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MCP-AI: Self-Learning API-to-cURL Model

@S-Umasankar

代码仓库

基本信息

分类

开发工具

传输方式

stdio

作者

S-Umasankar

关于 MCP-AI: Self-Learning API-to-cURL Model

暂无概览

MCP-AI: Self-Learning API-to-cURL Model 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "api-to-curl-mcp-server": {
      "command": "python",
      "args": [
        "src/ai_autonomous_dev.py"
      ]
    }
  }
}

MCP-AI: Self-Learning API-to-cURL Model 工具

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当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is 🚀 MCP-AI: Self-Learning API-to-cURL Model?

This project builds an autonomous AI system that converts API documentation into cURL commands. It uses reinforcement learning to self-improve and is deployed via an MCP server with continuous integration through GitHub Actions.

How to use 🚀 MCP-AI: Self-Learning API-to-cURL Model?

Install dependencies with pip install -r requirements.txt, then start the MCP server by running bash scripts/start_mcp.sh. Launch the AI automation with python src/ai_autonomous_dev.py, and test the system with pytest tests/.

Key features of 🚀 MCP-AI: Self-Learning API-to-cURL Model

  • Automated dataset generation from API documentation
  • Self-improving model with reinforcement learning
  • MCP server for API-based execution
  • Continuous deployment with GitHub Actions
  • Packaged as an SDK via setup.py
  • Includes pre- and post-training scripts (pre_train.py, post_train.py)

Use cases of 🚀 MCP-AI: Self-Learning API-to-cURL Model

  • Automatically generating cURL commands from any REST API documentation
  • Rapid prototyping and testing of API endpoints
  • Training and deploying a dedicated AI model for API-to-cURL conversion
  • Integrating cURL generation into CI/CD pipelines via the MCP server

常见问题

1

What are the main dependencies?

The `setup.py` requires FastAPI, Uvicorn, PyTorch, Transformers, sacrebleu, requests, pytest, and GitPython.

2

How do I start the MCP server?

Run `bash scripts/start_mcp.sh`. If `uvicorn` is not found, ensure it is installed (`pip install uvicorn`) and activate the Python virtual environment. Alternatively, modify the script to call `python -m uvicorn`.

3

How can I test the system?

Use `pytest tests/` after installing dependencies and starting the server.

4

What is the role of the MCP server?

It provides an API-based interface to execute the cURL generation model, enabling integration with other tools and workflows.

5

Does the server require authentication or configure a specific transport?

The README does not mention any authentication mechanism or transport configuration beyond the default Uvicorn HTTP server.

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